I am an Assistant Professor in the Department of Statistics. My research has four main focuses: (1) elucidating and completing the theory of likelihood-based inference for univariate extremes, (2) developing spatial extremes models that have flexible and realistic dependence properties,  (3) implementing these models efficiently for high-dimensional datasets with the help of high-performance computing and (4) developing useful real-life applications in climate science, hydrology, environmental statistics and neuroscience. These research topics range from building mathematical foundations for models to have accurate and flexible tail properties to executing the models on large spatial datasets. My research projects during the past five years have led to both the advancement of extreme value theory and interdisciplinary applications in climate science.